Stepwise least squares estimation of multivariate AR model
標(biāo)簽： multivariate estimation Stepwise squares
上傳時(shí)間： 2017-05-17
上傳用戶：pinksun9
建立了一種基于移動(dòng)最小二乘(Moving Least-Squares MLS)法的曲線曲 面擬合方法這種方法對(duì)傳統(tǒng)的最小二乘(LS)法的作了比較大的改進(jìn)使生成的曲線曲面具 有精度高光滑性好等許多優(yōu)點(diǎn)詳細(xì)介紹了移動(dòng)最小二乘法的原理應(yīng)用和特點(diǎn)并且給 出了使用移動(dòng)最小二乘法進(jìn)行曲線曲面擬合的程序設(shè)計(jì)流程最后給出了曲線擬合和空間散 亂數(shù)據(jù)曲面擬合算例將擬合結(jié)果與最小二乘擬合結(jié)果作了比較分析了MLS 擬合曲線曲 面的光滑性和擬合質(zhì)量表明了該方法的優(yōu)越性和有效性
標(biāo)簽： Least-Squares Moving MLS LS
上傳時(shí)間： 2017-07-02
上傳用戶：xc216
3D shape reconstruction matlab code. It used shape from defocus technique with least squares. You can reconstruct 3D shape with only two different depth images.
標(biāo)簽： shape reconstruction technique defocus
上傳時(shí)間： 2014-01-07
上傳用戶：Zxcvbnm
Least Squares Fitting of Data
標(biāo)簽： Fitting Squares Least Data
上傳時(shí)間： 2013-12-27
上傳用戶：問題問題
least squares method
標(biāo)簽： squares method least
上傳時(shí)間： 2014-01-25
上傳用戶：lifangyuan12
System identification with adaptive filter using full and partial-update Recursive-Least-Squares
標(biāo)簽： Recursive-Least-Squares identification partial-update adaptive
上傳時(shí)間： 2013-12-30
上傳用戶：LouieWu
MATLAB Example Code : Non-Linear Least Squares --- Bearings-Only Measurement
標(biāo)簽： Bearings-Only Measurement Non-Linear Example
上傳時(shí)間： 2014-06-08
上傳用戶：fxf126@126.com
We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.
標(biāo)簽： frequency-offset estimation quadrature amplitude
上傳時(shí)間： 2014-01-22
上傳用戶：牛布牛
·經(jīng)典Mean shift算法
上傳時(shí)間： 2013-05-29
上傳用戶：417313137
針對(duì)Mean Shift算法不能跟蹤快速目標(biāo)、跟蹤過程中窗寬的大小保持不變的特點(diǎn)。首先，卡爾曼濾波器初步預(yù)測目標(biāo)在本幀的可能位置；其次， Mean Shift算法在這點(diǎn)的鄰域內(nèi)尋找目標(biāo)真實(shí)的位置；最后，在目標(biāo)出現(xiàn)大比例遮擋情況時(shí)，利用卡爾曼殘差來關(guān)閉和打開卡爾曼濾波器。實(shí)驗(yàn)表明該算法在目標(biāo)尺度變化、遮擋等情況下對(duì)快速運(yùn)動(dòng)的目標(biāo)能夠取得較好的跟蹤效果。
標(biāo)簽： Shift Mean 卡爾曼濾波 車輛跟蹤
上傳時(shí)間： 2013-10-10
上傳用戶：TF2015
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